This work aims to integrate the concepts generated by a systematic literature review on patient flows in emergency departments (ED) to serve as a basis for developing a generic process model for ED.
A systematic literature review was conducted using PRISMA guidelines, considering Lean Healthcare interventions describing ED patients’ flows. The initial search found 141 articles and 18 were included in the systematic analysis. The literature analysis served as the basis for developing a generic process model for ED.
ED processes have been represented using different notations, such as value stream mapping and workflows. The main alternatives for starting events are arrival by ambulance or walk-in. The Manchester Triage Scale (MTS) was the most common protocol referred to in the literature. The most common end events are admission to a hospital, transfer to other facilities or admission to an ambulatory care system. The literature analysis allowed the development of a generic process model for emergency departments. Nevertheless, considering that several factors influence the process of an emergency department, such as pathologies, infrastructure, available teams and local regulations, modelling alternatives and challenges in each step of the process should be analysed according to the local context.
A generic business process model was developed using BPMN that can be used by practitioners and researchers to reduce the effort in the initial stages of design or improvement projects. Moreover, it’s a first step toward the development of generalizable and replicable solutions for emergency departments.
This paper explores how value chain governance affects the innovation performance of suppliers of intermediate products. We take advantage of a unique dataset of Italian firms to identify governance regimes based on the perceived levels of technological capabilities of suppliers and explicit coordination in the value chain. Our results indicate that ‘modular’ value chain governance is more conducive to innovation for suppliers, especially when these firms have medium capability levels. Conversely, market-based governance modes relate strongly to lower innovativeness amongst suppliers, particularly those with lower capabilities. These patterns are also reflected in the sales of innovative products. Our results go partially against other findings in the GVC literature, whereby relational value chains are usually seen as providing the most favorable environment for learning and innovation.
Despite the growing significance of virtual influencers (VIs) on social media, the utilisation of VIs in the tourism sector remains underexplored. Underpinned by the “computers are social actors” (CASA) paradigm and the Uncanny Valley theory, this study employed five focus groups with photo elicitation to investigate the key factors that inhibit audience engagement with VIs in tourism contexts. Embodiment (poor visual narrative, humanised content, and spillover effect from VI to content), the role of agency (ethical concerns and lack of relatability) and agent feature (uncanny appearance) were identified as primary impediments. While VIs are found to be alternative tourism endorsers in prevailing research, this study contributes to the literature by delineating the limitations of VIs in engaging with audiences, thereby providing critical insights for both scholars and practitioners. The findings consolidate the CASA paradigm by elucidating its boundary conditions, discerning the relationship between the CASA paradigm and the Uncanny Valley theory, and enabling practitioners to avoid pitfalls and adopt VIs more effectively.
Artificial intelligence (AI) is rapidly transforming the healthcare landscape, including the role of medical libraries. Understanding medical head librarians' perceived AI literacy and its potential impact on work performance is crucial for successful AI integration within medical institutions. This research aims to address this gap in knowledge by investigating the perceived AI literacy and its impact on the work performance of medical head librarians in Pakistan. The research adopted a quantitative survey method, utilizing a census method to approach the medical head librarians in Pakistan. Data collection was conducted through an online questionnaire administered to 124 medical head librarians employed in institutions recognized by the Pakistan Medical and Dental Council (PMDC) and the Higher Education Commission (HEC). The findings indicated that the medical head librarians displayed high levels of perceived AI literacy and work performance. Furthermore, the analysis revealed that AI literacy had a statistically significant and positive impact on work performance, suggesting that as medical head librarians' AI literacy increases, so does their work performance. These results provide valuable insights for governing bodies of medical institutions, AI developers, and other relevant stakeholders. The outcomes suggest that investing in AI-related training for medical librarians, creating user-friendly AI interfaces, and providing additional support from AI developers could play a crucial role in effectively implementing AI for information management in medical education in Pakistan. This study makes a significant contribution to the existing literature by addressing the paucity of research on AI literacy among medical librarians. Further research could deepen the understanding of AI literacy's impact on work performance and explore the mechanisms driving this relationship, offering additional guidance for policymakers and educators in enhancing AI-related skills among medical librarians.
Social media platforms like Instagram significantly influence tourists’ travel decisions by providing them with valuable insights, recommendations, authentic information, and points of interest. However, photos shared with location-specific hashtags, even those related to tourist attractions, do not always reflect the actual destination, creating challenges for potential visitors seeking accurate information. To assist tourists in finding pertinent tourism information for specific destinations, we propose VISTA: Visual Identification of Significant Travel Attractions. The proposed method employs deep learning and active learning techniques to automatically classify photos into: ‘Tourism-Related’ photos (i.e., photos related to tourism) and ‘Non-Tourism-Related’ photos (i.e., photos unrelated to tourism). To train our machine learning classifier, we created a dataset containing photos of the 10 most popular Israeli cities on Instagram. The classifier obtained an accuracy score of 0.965 and a weighted F1 score of 0.964. Evaluating our classifier’s global generalization on the InstaCities100K dataset, derived from InstaCities1M, yielded an accuracy score of 0.958 and a weighted F1 score of 0.959. The effectiveness of VISTA was demonstrated by comparing tourism-related and non-tourism-related photos in terms of photo proportion, user engagement, and object comparison. We found that most photos published on Instagram associated with cities are irrelevant to tourists and that tourism-related photos received more likes than non-tourism-related photos. Finally, there was a low overlap between objects in the two photo collections. Based on these results, we conclude that VISTA can help tourists tackle the problem of finding relevant tourism-related photos among the high volume of photos available on Instagram.
This study aimed to explore how non-disaster missioned organizations extend their roles to respond to disasters, which is referred to as ‘extending organization’ or Type III in the Disaster Research Center Typology. To achieve this, the current study investigated the formation conditions and evolution processes of extending organizations of a cooperative consumer organization, Gyeongju iCOOP (GiCOOP), which extended its roles by self-organizing a disaster-response team after the 5.8-magnitude earthquake that struck Gyeongju City, South Korea, 2016. Through a case study comprising in-depth interviews with GiCOOP members and public officials of central and local governments, this study found that the extending organization was successfully formed under several conditions, with the earthquake as a trigger and trustworthy relationships among the members, and evolved through diverse activities to strengthen community resilience capacity. Although the GiCOOP had sufficient financial resources and utilized external experts, its lack of workforce, expertise in disasters, and collaboration with local governments were critical hindrances in expanding its future activities. Based on these findings, several suggestions were made on the sustainability of extending organizations in the future.
The increasing usage of service robots in hotels has generated discussions about their positive impacts. However, little research has been done on the adverse aspects of robot usage from the perspective of the employees, and few studies have investigated the antecedents of employee robot risk awareness. This study posits that employees are aware of potential threats posed by robots; they observe the organization's investment in robot development and witness customers' satisfaction with robot usage. People with greater robot risk awareness engage in more withdrawal behaviors at work (employee sample in Study 1) and report lower intentions to work in the hospitality industry (student sample in Study 2). Those two relationships are further contingent upon employees' learning goal orientation. The proposed relationships were validated by a survey-based study (612 frontline employees) and two experiments (205 student participants). Based on the research results, hotels are encouraged to emphasize augmentation but not automation.
This study explores how breast cancer patients engage in travel and how travel may improve patients’ mental health. Data were collected from 31 breast cancer participants through interviews, and conventional content analysis was conducted. The results indicate that breast cancer patients participate in various travel activities that encompass natural, spiritual, interpersonal, cultural, and social aspects, and travel memories, including past travel nostalgia and future travel imagination. Using the chronic illness trajectory model, the study identifies three key healing roles of travel: mitigating death anxiety during the diagnosis stage, relieving psychological stress during the treatment stage, and promoting systematic recovery during the survivorship stage. These findings support the integration of travel-related interventions into the treatment and care of breast cancer patients. By facilitating these healing travel experiences, the tourism sector may play a crucial role in enhancing the quality of life for individuals facing serious health challenges.
Based on the approach/inhibition theory of power, this study explores the relationship between sense of power and exploitative leadership. We particularly examine the role of self-interest as a mediator and the role of ambition at work as a moderator.
The data were collected from 189 supervisors and 702 employees. We analyzed the data using path analysis to test the research model.
The results show the following: (1) sense of power positively affects exploitative leadership; (2) the effects of sense of power on exploitative leadership are mediated by self-interest; (3) the effects of self-interest on exploitative leadership are moderated by ambition at work.
The current study identifies self-interest as a key mediator that links sense of power to exploitative leadership and demonstrates that ambition at work moderates the process of self-interest to exploitative leadership.
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